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Industry 4.0 Skills Assessment: A Case Study of Students’ Perceptions in Computer Science Postgraduate Programs

  • Carlos Guzmán Sánchez-Mejorada
  • , Miguel Torres-Ruiz
  • , Rolando Quintero
  • , Kwok Tai Chui
  • , Giovanni Guzmán

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

With the appearance of Industry 4.0, the need for highly competent professionals in disruptive technologies and emerging intelligent computing is undeniable. In this way, education plays a crucial role in the success of sustainable development initiatives, as it must effectively integrate innovative practices, knowledge assurance, and new technologies. Thus, educational institutions must adjust the contents of their study plans to ensure that their graduates can successfully integrate into this constantly evolving work environment. In this paper, we present a study that identified how students at a computing research center perceived the relevance of the competencies and skills acquired during their studies to face the challenges of Industry 4.0. A survey was designed with 29 questions applied to a sample of 112 students of the Centro de Investigación en Computación, IPN. The results were analyzed statistically, and an inferential analysis concluded that the research hypothesis must be accepted. This study contributes to the global discussion on sustainable educational systems (SDG 4), demonstrating that student perception of their competencies for Industry 4.0 is mediated by integrating ethical and environmental principles in the curricula, a critical factor in Latin American contexts.

Original languageEnglish
Article number4974
JournalSustainability (Switzerland)
Volume17
Issue number11
DOIs
Publication statusPublished - Jun 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Industry 4.0
  • computing education
  • disrupting technologies
  • statistical analysis
  • sustainable education development

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